[GIS Interface In Oil Fields]

by

ACKNOWLEDGEMENT

I would take this opportunity to thank my research supervisor, family and friends for their support and guidance without which this research would not have been possible.

DECLARATION

I, [type your full first names and surname here], declare that the contents of this dissertation/thesis represent my own unaided work, and that the dissertation/thesis has not previously been submitted for academic examination towards any qualification. Furthermore, it represents my own opinions and not necessarily those of the University.

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ABSTRACT

The absence of detailed information on residential energy end use characteristics for the United States has in the past presented an impediment to the effective development and targeting of residential energy efficiency programs. This article presents a framework for modeling space heating, cooling, water heating, and appliance energy end uses, fuels used, and carbon emissions at a zip code-level resolution for the entire United States. It combines a regression-based statistical model derived from Residential Energy Consumption Survey data with U.S. census 2000 five-digit zip code level information, climate division-level temperature data, and other sources. The results show large variations in energy use characteristics both between and within different regions of the country, with particularly notable differences in the magnitude of and distribution by fuel of residential energy use in urban and rural areas. The results are validated against residential energy sales data and have useful implications for both residential energy efficiency planning and further study of variations in use patterns.

TABLE OF CONTENTS

ACKNOWLEDGEMENTII

DECLARATIONIII

ABSTRACTIV

CHAPTER 1: INTRODUCTION1

CHAPTER 2: LITERATURE REVIEW6

Geographic Information System6

OIL9

Representation and Perception15

Data Capture and Interoperability19

Spatial Data Modeling23

Cartography and Visualization27

CHAPTER 3: METHODOLOGY32

Specifying Regression Models for Each Energy End Use32

Utilizing Census Data to Achieve High Geographical Resolution32

Modeling Energy Use by Fuel Type33

CHAPTER 4: RESULTS AND ANALYSIS35

Model Validation35

Model Outputs39

CHAPTER 5: CONCLUSIONS41

REFERENCES43

CHAPTER 1: INTRODUCTION

To understand and model opportunities for oil fields to reduce energy use and carbon emissions, it is useful to have reasonably accurate estimates of how oil fields use energy and how they can best reduce their use. While this is often best accomplished by in-home audits and bottom-up engineering models of how a specific home functions, those approaches are often prohibitively expensive to scale and require large amounts of household-specific data. This research develops a high-resolution zip code-level estimate of the average residential energy use by fuel and end use category for the entire Middle East via an econometric model. In the absence of detailed home information, a spatially explicit model of residential energy use can serve as a first pass estimate of home energy end use characteristics and as a tool for targeting energy efficiency recommendations. It can also help identify spatial patterns in specific residential energy end uses and fuel consumption, and can be used to address questions of the effects of urban form and other factors on energy use (Yergin, 2003, 44).

Energy consumption in the residential sector represents approximately 22% of total MIDDLE EAST energy consumption and 21% of total carbon emissions. There is a paucity of detailed information about residential energy use vis-à-vis commercial, industrial, and transportation energy ...